Duties and Responsibilities of the Breeding Coordinator include:
Breeding process use-case gathering and documentation. Requires a knowledge of the application of genomics to breeding systems. Requires an ability to actively listen to and interpret users' needs, ask good questions to analyze the real need, identify gaps, find solutions, write clear and concise documentation and facilitate a shared understanding of the problem with the development team.
Lead integration of Breeding Insight system functions into breeding workflows, track adoption of the technology and study the impact of the system on the breeding programs.
Supervising and mentoring a Phenomics Coordinator, a Genomics Coordinator, and a Bioinformatics Coordinator.
Collaborating with Breeding Insight Developers and adjacent Cornell projects.
Develop workshop content and case studies, provide peer to peer training and instruction on the use of Breeding Insight system features.
Duties and Responsibilities of the Phenomics Coordinator include:
Coordinate with breeders at 5 breeding locations across the US (South Carolina, Oregon, West Virginia, New York, and Minnesota) to understand their breeding objectives, phenotyping needs, and manage project deliverables.
Work with PIs and breeders at USDA centers and universities to develop genomic breeding strategies, specify use-cases that clearly spell out the computational and interface requirements of the breeders, and form project plans to develop key capabilities and integrate Breeding Insight into the breeding programs.
Overall, combine these communications into a regular process coordinated with the development cycle implemented by the software team to ensure a well-defined roadmap of new methods and features.
In communication with breeders, design and help execute evaluation experiments and analyses of features introduced to the Breeding Insight on which follow-up requirement documents are based.
Duties and Responsibilities of the Software Developer include:
Code, test, debug, document and maintain highly complex programs or systems that make up the BIP stack under the direction of senior developers.
Collaborate with other software development teams to co-develop features needed by both teams.
Offer software support in the form of analyzing and amending software errors in a timely and accurate fashion, performing code reviews for peers, and maintaining, updating, and improving existing applications.
Ensure that test cases mimic external interfaces, implement automated testing routines to test functionality and stress, validate test routines and schedules, and evaluate code to ensure that it is valid, is properly structured, meets industry standards and is compatible with browsers, devices, or operating systems.
With the project team, be responsible for rapid cycle development of software, deployment in the cloud, coordination of genomic profiling, and integration with related initiatives at Cornell, nationally, and internationally.
Post-Doc with ARS Sweetpotato
Philip Wadl's group in Charleston, SC
The USDA, Agricultural Research Service, United States Vegetable Laboratory in Charleston, South Carolina, is seeking a POSTDOCTORAL RESEARCH ASSOCIATE, (Research Computational Biologist) for a TWO YEAR APPOINTMENT. Ph.D. is required. The salary is $64,009 per annum plus benefits. Citizenship restrictions apply.
The responsibilities of the position
Coordinate the development of data pipelines for high-throughput plant phenotyping and image analyses that will enhance specialty crop breeding programs at the USVL.
Develop image analysis and machine learning algorithms to facilitate the quantification of plant tolerance to biotic and abiotic stresses.
Develop data management protocols and systems that are capable of handling large volumes and different varieties of data, and work with a software development team to help develop graphical user interface (GUI) and standard application programming interface (API) for these systems.
Operation of various imaging systems and platforms, such as RGB, hyperspectral, and microscope-based.
Provide technical support, guidance, and training in image analysis and machine learning to USVL researchers.
Lead implementation and application of novel machine learning methodologies in plant phenotyping for vegetable crops at the USVL in collaboration with Breeding Insight. Breeding Insight is funded by the USDA, ARS through Cornell University.
Ph.D. degree in Agricultural and Biosystems engineering, computer/electronic engineering, information technology, computational biology, and other relevant background or proven hands-on experience in image analysis and machine learning.
Knowledge and experience in multiple programming languages and platforms (e.g. Python, C/C++, Fortran, Matlab, PlantCV, ImageJ, R).
Excellent communication and collaboration skills to work with plant biologists, IT support teams, engineers and algorithm developers.
Familiar with processing and analyzing RGB and hyperspectral imagery.
Strong knowledge and experience in data management, specifically in database applications, complex web applications, and storage technologies.
Familiarity and experience of applying statistical models to image processing a plus.
Qualified persons are requested to send a letter of application including a 1-page (maximum) statement of research goals, and a curriculum vitae as electronic PDFs along with email addresses for three references, and one representative example of their scholarly work to: